
AI Development Specialist
2 weeks ago
Job Overview:
We are seeking an experienced AI developer to design, implement, and maintain scalable, secure, and efficient cloud solutions for our AI initiatives.
The ideal candidate will have experience in NLP, predictive analysis, and CI/CD delivery pipeline, cost optimization, and cloud-native innovation.
Key Responsibilities:
- Understand specific requirements including data ingestion from different services, analytics needs, and user-facing application features.
- Lead technical discussions with cross-functional teams to evaluate feasibility, define specifications, and assess performance and scalability for solutions.
- Define and design software architecture for integrating data pipelines, ML models, and full stack applications.
- Drive deployment of end-to-end solutions from data collection and ML model deployment to web access with a focus on automation and resilience.
- Collaborate with cross-functional teams to design and deliver applications combining real-time data, machine learning, and cloud-native full stack platforms.
- Design, develop, and deploy scalable AI/ML models and systems to solve complex business problems across AWS and Azure.
- Optimize algorithms for performance, scalability, and accuracy.
- Evaluate and select appropriate AI tools, frameworks, and platforms.
- Work on data preprocessing and model evaluation.
- Ensure AI systems comply with standards.
- Contribute to code reviews, documentation, and technical presentations.
Required Skills and Qualifications:
- 6-8 years of experience in AI/ML development.
- Hands-on expertise in AI/ML frameworks like TensorFlow, PyTorch, or Keras.
- Hands-on expertise in Python, Java, or similar programming languages.
- Experience in cloud platforms AWS, Azure, or similar for deploying AI models.
- Expertise in NLP, deep learning, and other AI domains.
- Understanding of data structures, algorithms, and software engineering principles.
- Excellent problem-solving and collaboration skills.
- Bachelor's or Master's degree in Computer Science, IT, Engineering, or related fields.
Preferred Experience:
- Experience with MLOps and model deployment pipelines.
- Containerization (Docker, Kubernetes/EKS/AKS).
- Serverless architectures (Lambda/Functions).
- Experience working in Agile/Scrum environments.
- Experience with disaster recovery and enterprise-level high availability.
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